The Data4Diets platform was developed by the International Dietary Data Expansion (INDDEX) Project. The INDDEX Project strives to increase the availability, access, and use of dietary data through the development of an innovative data collection platform and demonstrating uses of existing consumption data for policies and programs. The objective of the Data4Diets platform is to aid program implementers, policy makers, and researchers to identify which diet-related food security indicators are best suited for their objectives, understand how the indicators should be constructed and used, and know which data sources and methods are preferred for producing these indicators, and access case study examples of how indicators have been analyzed to produce actionable policy information. The Data4Diets platform provides a searchable set of indicators, descriptions of common data sources and methods, links to guidelines for indicator construction, and concrete case studies illustrating ways in which each type of indicator has been leveraged for diet-related food security policy and programming.
The Data4Diets framework
The most widely accepted definition of food security derives from the 1996 World Food Summit, which describes food security as a “state in which all people, at all times, have physical and economic access to sufficient, safe and nutritious food to meet their dietary needs and food preferences for an active and healthy life” (FAO, 1996).
Experts agree that no single indicator can capture all of the dimensions of this definition. And yet, in practice, people commonly use single food security indicators without consideration of which dimensions of this definition are being captured (or not) by their chosen metric. Given the multidimensional nature of the food security construct, there has been continued debate about the best way to conceptualize, select, and organize the array of existing food security indicators. Most commonly, food security metrics reflect one of the “pillars” of availability, access, and utilization (and sometimes also stability) (USAID 1992, Webb and Rogers 2003). Others have chosen to group food security indicators by the unit of observation, such as national, market, household, and individual (Lele et al. 2016).
The Data4Diets platform follows a framework proposed by Coates (2013), which identifies six policy-relevant dimensions of the food security construct that are inherent to the1996 World Food Summit definition and were shown to reflect people’s own experience of the problem of food insecurity. The six food security components in the Data4Diets platform – slightly adapted from Coates (2013) – are: quantity (caloric sufficiency), quality (nutrient adequacy), preference, safety, stability, and sustainability, all of which can be measured at four levels (national, market, household, and individual) (Figure 1). The indicators in the D4D are considered “diet-related food security indicators” in that they measure whether food is sufficiently available, accessible, and utilizable to meet consumption needs (where needs include preference, quality, quantity, safety, stability, and sustainability). As such, the Data4Diets platform was developed to align with the INDDEX Project objective of expanding the use of consumption and dietary data worldwide.
Figure 1. Dimensions and levels for food security measurement
|National, Market (Available)|
|Market, Household, Individual (Accessible)|
|Household, Individual (Utilizable*)|
Indicators in the Data4Diets platform are categorized according to the dimension(s) to which they relate most closely**. Please see our FAQs and inclusion/exclusion criteria for further detail regarding the selection of indicators for the Data4Diets Platform.
*Note: 'Utilizable' in this context refers to individual food consumption. It can be examined, along with other information such as illness and biological use of nutrients, to understand the extent to which diet contributes to nutrition outcomes.
** Note: Not all food security indicators were designed to capture one of these 6 dimensions; many indicators are not specific to a single dimension, and therefore are presented under more than one dimension in the Data4Diets platform. Furthermore, this matrix approach highlights those dimensions where specific, accepted metrics are lacking – such as that of food preferences.
Understanding the ‘Dimensions’ and ‘Levels’ terminology in the Data4Diets
Food Security Dimensions:
The Data4Diets platform uses the terminology of ‘food security dimensions’ to refer to the different aspects of food security, as per the 1996 World Food Summit definition (FAO, 1996). Despite the multiple dimensions in the definition of food security, too frequently food security is measured using existing indicators that are either non-specific or only capture one piece of this multi-dimensional problem. As a result, some dimensions are rarely measured (e.g. safety, preferences) and users are often unclear which aspect of food security is actually captured by a given indicator. Coates (2013) asserts that a preferred approach is to develop and select indicators that specifically reflect each of these 6 dimension(s) to provide a holistic picture of the food security situation at a national, market, household or individual level. This approach should help to better diagnose the nature of food insecurity problems and develop solutions that are tailored to those problems. Thinking about food security through the lens of the different dimensions also highlights dimensions that have drawn the most policy attention (e.g. quantity and, increasingly, quality) and those that have been historically overlooked (e.g. safety and preference).
The food security dimensions in the Data4Diets are defined in the following way:
Quality: These indicators measure diet quality including aspects related to diversity, adequacy, moderation, and overall balance. Depending on the indicator, quality can range from considering the full dietary pattern and all foods/food groups or only specific macronutrients and micronutrients that are available, accessible, or consumed by the population of interest at national, market, household, and individual levels.
Quantity: These indicators relate to food sufficiency, primarily expressed as dietary energy (calories) that are available, accessible, or consumed by the population of interest at national, market, household, and individual levels.
Preference: These indicators relate to whether people are able to exercise the choice to consume foods that they prefer, i.e., those that are culturally and/or personally acceptable. Experiential food security scales (e.g. HFIAS, FIES) capture lack of choice by measuring people’s self-reported consumption behaviors in reaction to food access constraints. Proxy information could be used to infer choice constraints from purchasing behavior or experimental data at market, household, and individual levels.
Safety: These indicators relate to the safety of the food supply and food consumed as measured through foods available that are free of contamination or exposure (through consumption) to specific contaminants at national, market, household, and individual levels. More generally, food safety refers to the handling, preparation, and storage of foods that prevent food-borne illness.
Stability: These indicators relate to the inter- and intra-annual certainty and stability of food availability, access, and consumption – often in relation to food prices and other shocks -- at the national, market, household, and individual levels.
Sustainability: These indicators relate to the long-term future preservation and assurance of food availability, access and consumption at national, market, household, and individual levels for example through sustainable diets that could contribute to a reduced environmental impact.
Data Collection Levels:
The Data4Diets platform uses the terminology of ‘data collection levels’ to refer to the different levels at which the Data4Diets indicators are most commonly collected (national, market, household, individual). The data collection levels (national, market, household, individual) referred to in the Data4Diets platform correspond roughly to the food security pillars of availability, accessibility, and utilization of food as conceived in the historical approach to measuring food security. National and market level data can be used to measure the availability of food that is sufficient in terms of quantity and quality, stable, sustainable, safe, and meets consumer preferences. Market, household, and individual level data can be used to measure the accessibility of food that is sufficient in terms of quantity and quality, stable, sustainable, safe, and meets consumer preferences, while individual level data can be used to measure the utilization of food that meets these same criteria. (Note: 'Utilization' in this context refers to individual food consumption. It can be examined, along with other information such as illness and biological use of nutrients, to understand the extent to which diet contributes to nutrition outcomes).
The data collection levels in the Data4Diets are defined in the following way:
National: This level refers to data that are collected at the national level and represent national level averages (e.g. Food Balance Sheets) which cannot be disaggregated to lower data collection levels (i.e. units of analysis) like households and individuals.
Market: This level refers to data that are collected from a country’s domestic markets by monitoring prices (e.g. Vulnerability Analysis and Mapping) or purchasing behavior (e.g. Euromonitor). Market level data are often available at either a national or sub-national level.
Household: This level refers to data that are collected from and about households with sub-national representability (e.g. household consumption and expenditure surveys); these data can be aggregated up to the national level but cannot be used (without large assumptions) to draw conclusions about individual access and consumption of foods.
Individual: This refers to data that are collected at the individual level (e.g. quantitative 24-hour dietary recalls), which, if collected in a nationally (or regionally) representative way can be aggregated up to the national (or regional) level in order to draw conclusions about consumption patterns and preferences about the population in a region or country.
Winnie Bell (Researcher Data4Diets Lead, INDDEX)
Jennifer Coates (Principal Investigator, INDDEX)
Sarah McClung (Research Assistant, Tufts)
Caroline Nathan (Research Assistant, Tufts)
Tra Phuong Nguyen (Intern, Tufts)
Cathleen Prata (Senior Project Manager, INDDEX)
Beatrice Rogers (Co- Principal Investigator, INDDEX)
Nick Russell (Web Developer, Tufts)
Natalie Theys (Research Assistant, Tufts)
Gero Carletto (Technical Advisory Committee, INDDEX)
Elaine Ferguson (Technical Advisory Committee, INDDEX)
Yves Martin-Preval (Technical Advisory Committee, INDDEX)
Marie Ruel (Technical Advisory Committee, INDDEX)
Nadia Slimani (Technical Advisory Committee, INDDEX)
Anne Swindale (Technical Advisory Committee, INDDEX)
Anne Kepple (FAO)
Catherine Leclerq (FAO)
Ana Moltedo (FAO)
Nathalie Troubat (FAO)